Content area

Abstract

In this dissertation, I respond to existential questions about what the role of human writers will be in a world where generative AI (or GAI) tools like ChatGPT produce texts with limited human intervention. In the face of such fears about potentially constrained human rhetorical agency, one of the ways in which writers have been negotiating their agencies with GAI tools is through a new type of writing called “GAI prompts,” which refer to instructions that writers compose to elicit desired outputs from ChatGPT-like tools. Many early adopters of GAI in writing studies and allied fields have been publishing innovative rhetorical experiments in GAI prompt writing. The ability to compose prompts has also been advocated as a key skill within emerging frameworks for ‘AI literacy’ that seek to guide the adoption of GAI tools in an ethical and human-centered manner.

However, due to the nascent nature of this emerging form of writing, it remains undertheorized. To address this, I draw on genre theory, corpus methods, and virtue ethics to compile and study a corpus of GAI prompts published by early adopters of GAI in highly visible domains like journals and books in writing studies and allied fields. By analyzing this corpus using a mixture of qualitative and quantitative techniques, I provide a data-driven description of emerging genre characteristics of GAI prompts and present implications for how those data-driven descriptions can be used to support pedagogy, research, and UX design work in rhetoric, composition, and technical communication.

Details

Title
‘Learning to Talk to Generative AI Chatbots’: A Corpus Study of Generative AI Prompts, an Emerging Genre for AI Literacy
Author
Gupta, Anuj  VIAFID ORCID Logo 
Publication year
2025
Publisher
ProQuest Dissertations & Theses
ISBN
9798315749486
Source type
Dissertation or Thesis
Language of publication
English
ProQuest document ID
3212958400
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.